A Novel Heuristic Algorithm Integrating Battery Digital-Twin-Based State-of-Charge Estimation for Optimized Electric Vehicle Charging

The increasing need for effective electric vehicle (EV) charging solutions in the context of transportation electrification has become a significant challenge. This system introduces an innovative algorithm, named Energy Distribution and Node Allocation using Evolutionary and Resourceful Optimization (ENDEAVOR), designed to elevate the efficiency of EV charging through the integration of a battery’s digital twin. This cutting-edge algorithm offers precise estimations of EV charging time, seamlessly updating both the State of Charge (SOC) via the Unscented Kalman Filter (UKF) and the internal battery resistance using parameterization, while sending this information to the cloud. ENDEAVOR optimizes charging-node allocation and intelligently distributes energy among incoming EVs based on their specific charging requests, all within the context of renewable-energy-sourced charging stations. The incorporation of a digital twin for the battery confers several benefits, including highly accurate SOC and charging-time estimates that ultimately enhance the overall efficiency of the charging process. This algorithm further optimizes energy distribution, resulting in significantly improved charging-time predictions, reduced wait times for users, and an enhanced overall experience for the user. The day-to-day implications of these enhancements are remarkable, culminating in substantial annual energy savings of approximately 180 units. ENDEAVOR has the potential to revolutionize the landscape of EV charging.